Method and system for determining a risk of hemodynamic compromise after cardiac intervention

ABSTRACT

A method and system for predicting a measure of hemodynamic compromise as a result of transcatheter cardiac treatment. The method includes providing a patient-specific anatomical model representing cardiac region and an implant model representing a three-dimensional representation of a cardiac implant. The method includes virtually deploying said implant model into said patient-specific anatomical model. A deformation of the patient-specific anatomical model is calculated as a result of implant model deployment A measure of hemodynamic compromise is determined from the virtually deployed implant model and the deformed patient-specific anatomical model.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/361,156, filed Jun. 28, 2021, now U.S. Pat. No. 11,331,149, which isa continuation of U.S. patent application Ser. No. 17/003,653, filedAug. 26, 2020, now U.S. Pat. No. 11,051,885, which is a continuation ofU.S. patent application Ser. No. 16/482,509, filed Jul. 31, 2019, nowU.S. Pat. No. 11,045,256, which is a national phase application under 35U.S.C. § 371 of PCT/EP2018/052701, filed Feb. 2, 2018, which claimspriority to European Patent Application Serial No. 17154648.4, filedFeb. 3, 2017, and is also a continuation-in-part of U.S. patentapplication Ser. No. 14/399,781, filed Nov. 7, 2014, now U.S. Pat. No.10,789,772, which is a national phase application under 35 U.S.C. § 371of PCT/EP2013/058392, filed Apr. 23, 2013, which claims priority toPCT/EP2013/054276, filed Mar. 4, 2013, and PCT/EP2012/059207, filed May16, 2012, the entire contents of each of which are incorporated hereinby reference. U.S. patent application Ser. No. 17/361,156, filed Jun.28, 2021, now U.S. Pat. No. 11,331,149, is also a continuation-in-partof U.S. patent application Ser. No. 15/570,976, filed Oct. 31, 2017, nowU.S. Pat. No. 11,141,220, which is a national phase application under 35U.S.C. § 371 of PCT/EP2016/059688, filed Apr. 29, 2016, which claimspriority to European Patent Application Serial No. 15166130.3, filed May1, 2015, the entire contents of each of which are incorporated herein byreference.

FIELD OF THE INVENTION

The present invention relates to the field of pre-operative planning oftranscatheter structural heart interventions, e.g. valve treatment, suchas valve implantation and/or repair. More in particular, the inventionrelates to pre-operative prediction of the risk a patient developinghemodynamic compromise as a result of transcatheter valve treatment.

BACKGROUND TO THE INVENTION

The left ventricle of the heart pumps the blood to the aorta through theaortic valve. Aortic (valve) stenosis is a pathology occurring when theaortic valve does not open fully because the leaflets calcify, thickenand stiffen and, as a result, the blood flow going from the heart to thesystemic circulation decreases. Aortic stenosis manifests itself inelderly people, with a prevalence going from 1.3% in over 65 and 4% inover 85 year old people. Currently it is one of the most common valvularheart diseases in the Western world and its prevalence is increasingwith the aging population. The traditional treatment for an aorticstenosis is the Surgical Aortic Valve Replacement (SAVR) aiming atreproducing the correct function of the native valve with an implantedvalve. This invasive procedure requires total anesthesia, sternotomy(open-heart surgery) and cardiopulmonary bypass (the blood is pumped andoxygenated using an external machine), and is associated with about 6%in-hospital mortality for over 65 year old patients. Moreover, at leastone-third of the patients with severe aortic stenosis are denied valvesurgery as the risks associated with surgery are too high.

Trans-catheter aortic valve implantation (TAVI) or trans-catheter aorticvalve replacement (TAVR) is a minimally-invasive procedure for treatingaortic stenosis: (1) the valve (e.g. a bioprosthetic valve made ofporcine pericardium sutured on a metal stent) is crimped inside acatheter, (2) the catheter is inserted, for example, in the femoralartery, (3) pushed upstream along the aorta up to the aortic annulus and(4) the new valve is deployed within the diseased native valve. TAVI hasthe potential of treating high-risk patients and replacing the SAVR witha minimally-invasive intervention (no need for open-heart surgery orcardiopulmonary bypass) which can be performed in e.g. about 80 minutes.Main TAVI complications are vascular injury, stroke, cardiac injury(heart block, coronary obstruction, cardiac perforation), aorticregurgitation, cardiac conduction abnormalities and valve misplacement.Accurate pre operative planning is crucial to select the optimal devicesize and to anticipate potential difficulties.

Undersizing of a valve implant may lead to paravalvular aorticregurgitation, while oversizing may result in a rupture of the aorticannulus or in a suboptimal functional behavior of the implant (e.g.central regurgitation) or in conduction disturbances or in coronaryobstruction. Currently available planning tools (Philips, Siemens, PieMedical, Paeion) provide insights into the patient anatomy and can, forexample, be used to determine the size of the aortic annulus, or tomeasure the distance between the valve plane and the coronary ostia. Aproblem with these tools is that they do not provide preoperativeinsights into the interaction between a certain implant device and thespecific patient anatomy, and can thus not be used to predictcomplications such as regurgitation. Such insights are extremelyvaluable for interventional cardiologists.

Document US 2011/0153286 A1 discloses a method and system for virtualpercutaneous valve implantation. In one embodiment of the application apatient-specific anatomical model of a heart valve is estimated based on3D cardiac medical image data. An implant model representing a valveimplant is virtually deployed into the patient-specific anatomical modelof the heart valve. A library of implant models, each modelinggeometrical properties of a corresponding valve implant, can bemaintained. The implant models maintained in the library can bevirtually deployed into the patient specific anatomical model of theheart valve to select one of the implant models for use in apercutaneous valve implantation procedure.

US 2011/0153286 A1 does not provide a prediction of the mechanicalbehavior and interaction of the patient-specific aortic root, ascendingaorta and aortic valve leaflets with the deployment of a valve implant.Said document also does not account for calcification of aortic valveleaflets. Neither does it provide a means to study the hemodynamicperformance of an implant deployed in the aortic valve.Balloon-expandable devices whose deployment is based on permanentplastic deformations of the metal cannot be modeled. There is a need formore precise valve sizing and positioning. Problem is that the aorticannulus is not circular, that the aortic annulus may deform and thatcalcium deposits may deform a valve frame. Another problem is that theaortic root visualized with Computed Tomography (CT) imaging changes inshape and size after TAVI. Also the geometry of the stent frame of thetranscatheter aortic valve (TAV) is affected by the stiffness of theaortic root, by the presence of stiff calcified regions and by the exactdevice position.

Sub-optimal treatment planning can have two socio-economic effects. Onthe one hand this gives higher costs for the health system. If theincorrect device/size of the TAV is chosen, the first TAVI procedure mayfail and additional treatments, including a second TAVI procedure(valve-in-valve), SAVR, or rehospitalization may be necessary, with aconsiderable increase of the costs per patient. As a reference, onesingle TAVI procedure costs about 40 k Euro and the stented valve itselfcosts about 20 k Euro. On the other hand this leads to a lowerprognosis. Sub-optimal treatment planning may result in peri-proceduralcomplications, which affect both the life quality and the lifeexpectancy of the patient. An oversized valve may rupture the annulus ordissect the aorta whereas an undersized valve may dislodge and migrateor can induce paravalvular regurgitation.

In WO2013/171039 A1 the present inventors described a solution toovercome at least part of the above-mentioned disadvantages.WO2013/171039 A1 provides an improved method for preoperative insightsinto the interaction of an implant device and specific patient anatomy,for better prediction of complications, such as regurgitation, forbetter prediction of the hemodynamic performance of an implant deployedin an aortic valve, and for better patient selection and stratification.Also WO2013/171039 A1 provides a web-based pre-operative planningservice for TAVI using computer simulations that predict stent framedeformation and incomplete frame apposition, allowing to assess the riskof regurgitation and other complications such as coronary obstructionand conduction abnormalities prior to the intervention.

In WO2016/177647 A1 the present inventors described method fordetermining a measure of a risk of a patient developing cardiacconduction abnormalities and/or disorders, such as left bundle-branchblock (LBBB), as a result of transcatheter structural heartintervention, such a transcatheter cardiac valveimplantation/replacement or repair.

SUMMARY OF THE INVENTION

Transcatheter mitral valve replacement, TMVR, may lead to an obstructionof the left ventricular outflow tract, LVOT, so blood flow towards theaorta may be significantly reduced. TMVR may also lead to acompression/obstruction of the left circumflex coronary artery, LCX,and/or the coronary sinus. It has been found that LVOT obstruction afterTMVR in patients with mitral annular calcification occurs inapproximately 10% of the patients. TAVI may lead to an obstruction ofthe coronary arteries, due to the movement of the calcified nativeleaflets towards the coronary ostia, or due to the presence of the TAVitself. Coronary obstruction after TAVI occurs in 0.5-1% of cases.

Thus, transcatheter cardiac valve implantation/replacement or repair canlead to hemodynamic compromise. The hemodynamic compromise can beobstruction of a primary blood flow path in which the valve isimplanted. Such obstruction can cause a drop (gradient) in bloodpressure over the implanted device. The hemodynamic compromise can beobstruction of a secondary blood flow path in communication with theprimary blood flow path, e.g. at the location of the implanted device.The hemodynamic compromise can be leakage (or regurgitation) with occursin the primary blood flow path.

Hence, there is a need to predict hemodynamic compromise, such asobstruction and/or leakage, as a result of valve treatment. Hence, aphysician can preoperatively predict whether, and to what extent, aprocedure such as valve replacement will result in complications such asobstruction of an adjacent blood flow path, such as the LVOT, LCX,coronary sinus, or coronary artery.

According to an aspect is provided a method for predicting a measure ofhemodynamic compromise as a result of transcatheter structural heartintervention, such a transcatheter cardiac valve treatment. Thetreatment may be trans-catheter valve implantation/replacement ortrans-catheter valve repair. The transcatheter cardiac valve may e.g. bea transcatheter aortic or mitral valve or tricuspid valve. The methodincludes providing an implant model representing a three-dimensionalrepresentation of a cardiac implant, such as a cardiac valve implant,e.g. an aortic valve implant or mitral valve implant. The implant modelcan represent a three-dimensional representation of a transcathetermitral valve, TMV, or transcatheter aortic valve, TAV, or transcathetertricuspid valve. The implant model can be a finite elementrepresentation of the cardiac implant. The method includes providing apatient-specific anatomical model representing a patient-specificcardiac region including a deployment site for the cardiac implant in afirst blood flow path, such as a patient-specific cardiac valve region,and a second blood flow path, such as a LVOT or aorta. Thepatient-specific anatomical model may represent a patient-specific leftventricle and/or atrium and/or aorta or a part thereof. Thepatient-specific anatomical model can comprise a finite element mesh.The implant model is virtually, e.g. in silico, placed, e.g. deployed,into the patient-specific anatomical model at the deployment site. Adeformation of the patient-specific anatomical model as a result ofimplant model deployment is calculated. From the virtually deployedimplant model and the deformed patient-specific anatomical model, ameasure of hemodynamic compromise in the deformed patient-specificanatomical model is determined. On the basis of the determined measureof hemodynamic compromise, a measure may be determined of the risk ofthe patient developing complications if an actual implant correspondingto the implant model were actually implanted in the anatomical region ofthe patient corresponding to the patient-specific anatomical model.

The method can be used for predicting obstruction of the second bloodflow path. Then, from the virtually deployed implant model and thedeformed patient-specific anatomical model, a measure of obstruction ofthe second blood flow path in the deformed patient-specific anatomicalmodel is determined. On the basis of the determined measure ofobstruction, a measure may be determined of the risk of the patientdeveloping complications if an actual implant corresponding to theimplant model were actually implanted in the anatomical region of thepatient corresponding to the patient-specific anatomical model.

The method can be used for predicting obstruction of the first bloodflow path. For example, it is possible that with the valve leaflets openan open area of the valve is reduced, e.g. due to a not well expanded ordeployed valve. This can cause a pressure drop (or gradient) in theblood flow through the valve. Then, from the virtually deployed implantmodel and the deformed patient-specific anatomical model, a measure ofobstruction of the first blood flow path in the deformedpatient-specific anatomical model is determined. On the basis of thedetermined measure of obstruction, a measure may be determined of therisk of the patient developing complications if an actual implantcorresponding to the implant model were actually implanted in theanatomical region of the patient corresponding to the patient-specificanatomical model.

The method can be used for predicting leakage in the first blood flowpath. For example, it is possible that with the valve leaflets closedblood leaks around the outside of the implanted valve, between the valveand the surrounding tissue. Alternatively, or additionally, in theclosed position the valve leaflets may not fully close, allowing bloodto leak through the implanted valve. Then, from the virtually deployedimplant model and the deformed patient-specific anatomical model, ameasure of leakage in the first blood flow path in the deformedpatient-specific anatomical model is determined. On the basis of thedetermined measure of leakage, a measure may be determined of the riskof the patient developing complications if an actual implantcorresponding to the implant model were actually implanted in theanatomical region of the patient corresponding to the patient-specificanatomical model.

It will be appreciated that the method includes computer implementedsteps. It will be appreciated that all above mentioned steps can becomputer implemented steps.

A cardiac valve implant and a cardiac valve region of the patient is animportant example of the present invention. Nevertheless, the inventioncan also be applied to other implants, such as stents. Although below isreferred in particular to a cardiac valve implant and a cardiac valveregion of the patient, it will be appreciated that the features andadvantages also apply to other implants for the heart. Therefore, forthe purpose of understanding the invention where herein is referred to acardiac valve implant and cardiac valve region this similarly holds forother cardiac implants and/or other cardiac regions, including LAA,atrial or ventricular septal defect closure.

Optionally, the method includes providing the patient-specificanatomical model at a plurality of moments during the cardiac cycle, anddetermining the measure of hemodynamic compromise, at the plurality ofmoments. It will be appreciated that the geometry of the heart changessignificantly during the cardiac cycle. Therefore, the measure ofhemodynamic compromise may vary significantly during the cardiac cycleas well. Hence, determining the measure of hemodynamic compromise at aplurality of moments during the cardiac cycle allows to determineminimum and maximum values of the hemodynamic compromise.

Optionally, the measure of obstruction of the second blood flow path isa cross sectional area of the second blood flow path. The crosssectional area, for instance, e.g. substantially, orthogonal to thedirection of blood flow has proven to be a reliable measure ofobstruction. The cross sectional area of the second blood flow pathafter deployment of the implant model can be compared with a crosssectional area of the second blood flow path in the patient-specificanatomical model in which no implant model is deployed. This providesinsight into the predicted change of cross sectional area available forblood flow after deployment of the implant. Also a volume reduction of asegment of the second blood flow path can be a good measure to quantifyobstruction.

Optionally, the measure of obstruction of the second blood flow path isa ratio of a cross sectional area of the second blood flow path when theimplant model is deployed divided by a cross sectional area of thesecond blood flow path in the patient-specific anatomical model in whichno implant model is deployed. This takes into account deformation of theanatomy, e.g. a TMVR device pushing against the LVOT reducing LVOT area,and presence of the device, e.g. the remaining area is the deformed areaminus area occupied by the device. The ratio provides insight into thepredicted change of the cross sectional area due to implant deployment.

Optionally, the measure of obstruction of the first blood flow path is across sectional area of the first blood flow path, e.g. in view of valveleaflet positions. The cross sectional area, for instance, e.g.substantially, orthogonal to the direction of blood flow has proven tobe a reliable measure of obstruction. The cross sectional area of thefirst blood flow path after deployment of the implant model can becompared with a cross sectional area of the first blood flow path in thepatient-specific anatomical model in which no implant model is deployed.This provides insight into the predicted change of cross sectional areaavailable for blood flow after deployment of the implant. Also a volumereduction of a segment of the first blood flow path can be a goodmeasure to quantify obstruction.

Optionally, the measure of obstruction of the first blood flow path is aratio of a cross sectional area of the first blood flow path when theimplant model is deployed divided by a cross sectional area of the firstblood flow path in the patient-specific anatomical model in which noimplant model is deployed. The ratio provides insight into the predictedchange of the cross sectional area due to implant deployment.

Optionally, the patient-specific anatomical model further includes fluidpressures in the cardiac region. Hence, deformation of thepatient-specific anatomical model can be calculated taking into accountthe fluid pressure. It is also possible to use computational fluiddynamics, CFD. Hence, obstruction and/or leakage can be determined.

Optionally, the method includes the step of simulating a displacement ofat least one valve leaflet of the cardiac valve implant. The measure ofhemodynamic compromise, e.g. the measure of obstruction of the secondblood flow path, can then be determined also on the basis of the leafletdisplacement.

Optionally, the method includes the step of simulating a displacement ofat least one valve native leaflet due to device-anatomy interaction andoptionally hydrodynamic forces. The measure of hemodynamic compromise,e.g. the measure of obstruction of the second blood flow path, can thenbe determined also on the basis of the leaflet displacement.

Optionally, the displacement of the valve leaflet (of the implant and/ornative valve) can be calculated using CFD, or fluid structureinteractions, FSI. For example, the anterior mitral valve leaflet isdisplaced towards the LVOT by TMVR, but may further move during systoledue to blood flow. This may be modelled as suggested.

Optionally, the measure of obstruction of the second blood flow path isa pressure gradient at the second blood flow path. Optionally, themeasure of obstruction of the first blood flow path is a pressuregradient at the first blood flow path. Optionally, the measure ofobstruction of the first blood flow path is a pressure gradient acrossthe implant, e.g. the valve (i.e. non-zero pressure difference acrossthe valve when valve is open).

Optionally, the measure of obstruction of the second blood flow path isa flow measure at the second blood flow path. Optionally, the flowmeasure is the maximum velocity at the second blood flow path or theextension of the cross sectional portion of the second blood flow pathwith velocity magnitude above a threshold. Optionally, the measure ofobstruction of the first blood flow path is a flow measure at the firstblood flow path. Optionally, the flow measure is the maximum velocity atthe first blood flow path or the extension of the cross sectionalportion of the first blood flow path with velocity magnitude above athreshold.

It will be appreciated that this method provides the advantage that themeasure of the risk of the patient developing hemodynamic compromise,such as obstruction and/or leakage, as a result of transcathetertreatment of the cardiac valve can be predicted pre-operatively. Hence,it is possible to predict how likely e.g. a planned TAVI or TMVRprocedure will result in hemodynamic problems.

Optionally, determining the measure of hemodynamic compromise includesdetermining an evolution of the hemodynamic compromise over time duringthe process of deployment. It is possible to determine the measure ofhemodynamic compromise at a first moment and at a second moment. Thefirst moment may be prior to the implant model being fully deployed intothe patient-specific anatomical model. The second moment may be afterthe implant model has been fully deployed into the patient-specificanatomical model. It is also possible to determine the measure of thehemodynamic compromise at a plurality of first moments. Hence a timeevolution of the hemodynamic compromise during deployment of the implantmodel can be determined. Optionally, time evolution of hemodynamiccompromise after deployment is also determined. Hence, remodeling of theheart, due to the heart anatomy changing due to the prolonged presenceof the implant, can be taken into account. For instance, hemodynamiccompromise at one week, at one month, and at one year after treatmentcan be determined.

Optionally, determining the measure of hemodynamic compromise mayinclude determining a series of situations of progressing deployment ofthe implant model into the patient-specific anatomical model. Thesituations may progressively differ by a predetermined amount or ratioof deployment. The deployment can include insertion of the implant modelinto the patient-specific anatomical model. The insertion can includetravel of a model of a, collapsed, implant along a vessel. The series ofsituations can include situations of progressively differing positionsof insertion up to an intended deployment position. The deployment caninclude expansion of the implant model in the patient-specificanatomical model. The series of situations can include situations ofprogressively differing stages of expansion of the implant model. Foreach of the situations of the series of situations the measure ofhemodynamic compromise can be determined as described above. Hence, allstages of deployment can be modeled. The processing unit can be arrangedto determine the situation of the series of situations in which thedetermined hemodynamic compromise is most significant, e.g. highestobstruction. The processing unit may be arranged to determine themeasure of hemodynamic compromise in the situation of the series ofsituations in which the determined mechanical interaction is mostsignificant for predicting hemodynamic problems, e.g. highest. Theseries of situations may be generated for a plurality of differentdeployment sites. The processing unit may be arranged to select theoptimum deployment site.

It will be appreciated that the risk of the patient developinghemodynamic problems can be quantified by taking a combination of thedeterminations mentioned above.

Optionally, the method includes estimating the patient-specificanatomical model on the basis of a, preferably preoperative,cardiovascular 2D or 3D or 4D medical image data, such as a X-rays,CT-scan, an MRI image, echocardiography images or the like, andcombinations thereof.

Optionally, the method includes estimating the patient-specificanatomical model on the basis of anatomical measurements, using forexample, a parametric heart model.

Optionally, the implant model comprises a finite element mesh. Eachelement of said mesh can be featured by a set of nodes. Adjacentelements of said element can comprise mutually shared nodes with saidelement. Said element can be featured by material dependent parameters.Each element of said mesh can differ in material dependent parametersfrom an adjacent element of said element of said mesh.

Optionally, stiffness elements are provided to a plurality of nodes of amesh of the anatomical model. A stiffness element induces a reactingforce on the corresponding node of said mesh, wherein said force isdependent on the displacement of said node or on the distance betweensaid node and a fixed position equal or very close to the initialposition of said node.

Optionally, the step of virtually deploying the implant model into thepatient-specific anatomical model includes a three-dimensional finiteelement analysis. Hence, deployment of the implant in thepatient-specific anatomical model can be simulated in silico in threedimensions.

Optionally, the method includes virtually deploying the implant modelinto the patient-specific anatomical model at a plurality of differentlocations at and/or near the deployment site and determining the measureof obstruction of the second blood flow path for each of the differentlocations. Hence, it is possible to assess the risk of hemodynamicproblems for the plurality of different locations of the implant. Hence,it is also possible to select the location for the implant associatedwith the lowest risk of developing hemodynamic obstruction problems.Such selected location can be used in pre-operative planning of a TAVIor TMVR procedure.

Optionally, the step of virtually deploying the implant model includesproviding a plurality of implant models, each modeling geometricaland/or material properties of a corresponding implant; and virtuallydeploying each of the implant models into the patient specificanatomical model, and determining the measure of hemodynamic compromisefor each of the implant models. Hence, it is possible to assess the riskof hemodynamic problems for each the plurality of different implantmodels. Hence, it is also possible to select the implant modelassociated with the lowest risk of developing hemodynamic obstructionproblems. Such selected implant model can be used in pre-operativeplanning of a TAVI or TMVR or TTVR procedure. The method can includeselecting a cardiac valve implant corresponding to one of the pluralityof the implant models for a percutaneous implantation procedure. Acardiac valve implant associated with the selected implant model can beused in a percutaneous implantation procedure to minimize risk of thepatient developing hemodynamic problems. It will be appreciated that itis also possible to virtually deploy each implant model of the pluralityof implant models into the patient specific anatomical model at aplurality of different locations at and/or near the deployment site.Thus the implant models can be compared each at its optimal location.

Optionally, the method includes reporting the measure of hemodynamiccompromise to a user. The measure of hemodynamic compromise, e.g. themeasure of obstruction and/or leakage, may e.g. be displayed on adisplay, printed in hardcopy or the like. It is also possible to reportan indication of the risk of the patient developing hemodynamic problemsto the user.

According to an aspect is provided a system for determining, e.g.predicting, a measure of hemodynamic compromise as a result oftranscatheter cardiac valve treatment. The system includes a processor.The processor is arranged for receiving an implant model representing athree-dimensional representation of a cardiac valve implant. Theprocessor is arranged for receiving a patient-specific anatomical modelrepresenting a patient-specific cardiac region including a deploymentsite for the cardiac implant in a first blood flow path and a secondblood flow path. The patient-specific anatomical model can comprise afinite element mesh. The processor is arranged for virtually deployingsaid implant model into said patient-specific anatomical model at thedeployment site. The processor is arranged for calculating deformationof the patient-specific anatomical model as a result of implant modeldeployment. The processor is arranged for determining, from thevirtually deployed implant model and the deformed patient-specificanatomical model, a measure of hemodynamic compromise in the deformedpatient-specific anatomical model. The processor can be arranged fordetermining a measure of risk of the patient developing hemodynamicproblems on the basis of the determined measure of hemodynamiccompromise. Thus, the system can be used to perform the method asdescribed above.

According to an aspect is provided a computer program product includingcomputer implementable instructions. The computer program product can bestored on a non-transient data carrier. When implemented by aprogrammable computer the instructions cause the computer to retrieve animplant model representing a three-dimensional representation of acardiac valve implant. When implemented by a programmable computer theinstructions cause the computer to retrieve a patient-specificanatomical model representing a patient-specific cardiac regionincluding a deployment site for the cardiac implant in a first bloodflow path and a second blood flow path. The patient-specific anatomicalmodel can comprise a finite element mesh. When implemented by aprogrammable computer the instructions cause the computer to virtuallydeploy said implant model into said patient-specific anatomical model atthe deployment site. When implemented by a programmable computer theinstructions cause the computer to calculate deformation of thepatient-specific anatomical model as a result of implant modeldeployment. When implemented by a programmable computer the instructionscause the computer to determine, from the virtually deployed implantmodel and the deformed patient-specific anatomical model, a measure ofhemodynamic compromise in the deformed patient-specific anatomicalmodel. When implemented by a programmable computer the instructions cancause the computer to determine a measure of risk of the patientdeveloping hemodynamic problems on the basis of the determined measureof hemodynamic compromise. Thus, the computer program product can beused to perform the method as described above.

It will be appreciated that all features and options mentioned in viewof the method apply equally to the system and the computer programproduct. It will also be clear that any one or more of the aboveaspects, features and options can be combined.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention will now be described in detailwith reference to the accompanying drawings in which:

FIG. 1 is schematic representation of a system;

FIG. 2 is a schematic example in which an implant model and apatient-specific anatomical model are represented; and

FIGS. 3a, 3b, 3c are an example wherein the implant model is deployedinto the patient-specific anatomical model at a plurality of differentlocations.

DETAILED DESCRIPTION

Left ventricular outflow tract (LVOT) obstruction after a transcathetermitral valve replacement (TMVR) procedure is a frequent complication.LVOT obstruction after TMVR in patients with mitral annularcalcification may occur in approximately 10% of the patients. This canresult in increased mortality after one year. Using the presenttechnology, however, a predictor for the occurrence of LVOT obstructionor other hemodynamic compromise can be given.

FIG. 1 shows a schematic example of a system 1 for predicting a measureof hemodynamic compromise, such as obstruction of a blood flow path, asa result of transcatheter cardiac valve treatment. The system includes aprocessing unit 2. The processing unit 2 includes a first receiving unit4 for receiving a patient-specific anatomical model. Here thepatient-specific anatomical model represents a patient-specific cardiacvalve region.

In this example, the patient-specific anatomical model is provided as athree dimensional (3D) finite element model comprising a finite elementmesh. In this example the patient-specific anatomical model is receivedfrom a conversion unit 6. The conversion unit 6 is arranged forreceiving medical imaging data from a medical imaging device 8. Themedical imaging data may be 2D, 2.5D (stacked 2D), 3D or 4D imagingdata. The medical imaging data may be preoperative imaging data. Themedical imaging device 8 may e.g. be a X-ray scanner, computertomography (CT) device, an echocardiography device or a magneticresonance imaging (MRI) device. In this example, the conversion unit 6is arranged for creating the patient-specific 3D finite element model onthe basis of the medical imaging data. Alternatively, or additionally,the patient-specific anatomical model can be received from a database10.

The processing unit 2 further includes a second receiving unit 14arranged for receiving an implant model representing a 3D representationof a cardiac valve implant, here a finite element representation. The 3Drepresentation of the cardiac valve implant may e.g. be received from a3D modelling system 16. Alternatively, or additionally, the 3Drepresentation of the cardiac valve implant can be received from adatabase 18.

FIG. 2 shows a schematic example of a patient-specific anatomical model40 of a cardiac valve region. FIG. 2 also shows a schematic example ofan implant model 42. In this example the implant model 42 represents amitral valve implant. The patient-specific anatomical model 40 includesa deployment site 44 for the cardiac implant 42 in a first blood flowpath 46. The patient-specific anatomical model 40 also includes a secondblood flow path 48. The first blood flow path 46 can e.g. be a bloodflow path extending through the mitral valve, while the second bloodflow path 48 is the LVOT. In another example, the first blood flow pathcan e.g. be a blood flow path extending through the aortic valve, whilethe second blood flow path is a coronary artery.

Returning to FIG. 1, the processing unit 2 includes a placing unit 20arranged for virtually deploying said implant model into saidpatient-specific anatomical model. The placing unit can place theimplant model 42 into the patient-specific anatomical model 40. Theplacing unit 20 can be arranged for bringing the implant model and thepatient-specific anatomical model in a common model space. Theprocessing unit 2 can be arranged for defining a deployment site 44 forthe implant model in the first blood flow path 46 in thepatient-specific anatomical model 40. The processing unit can include aninput unit 19 arranged for receiving information relating to thedeployment site 44. The input unit 19 can be associated with a graphicaluser interface arranged for allowing a user, such as a surgeon, to inputa desired deployment site 44 for the implant model 42 in thepatient-specific anatomical model 40. It is also possible that theprocessing unit 2 is arranged for autonomously determining, orproposing, the deployment site 44. The determined or proposed deploymentsite 44 can be based on a rule. The rule can be associated with apredefined location of an anatomical structure in the patient-specificanatomical model 40. The placing unit 20 can apply three dimensionalfinite element analysis.

The placing by the placing unit 20 also includes virtually expanding theimplant model 42 into the patient-specific anatomical model 40. Theexpanded implant model 42 will abut against the patient-specificanatomical model 40. It will be appreciated that the patient-specificmodel 40 may deform, e.g. locally, due to the presence of the, e.g.expanded, implant model 42.

The processing unit 2 here includes a calculation unit 21 arranged forcalculating a deformation of the patient-specific anatomical model 40 asa result of implant model 42 deployment. It will be appreciated thatphysical properties, such as stiffness, associated with both the implantmodel and the patient-specific anatomical model will determine the shapeof the expanded implant model 42, the corresponding shape of thedeformed patient-specific anatomical model 40, and a mechanicalinteraction between the implant model and the patient-specificanatomical model. The mechanical interaction can include one or more offorce, pressure, stress, and strain between the implant model and thepatient-specific anatomical model.

The processing unit 2 further includes a determination unit 22 arrangedfor determining, from the virtually deployed implant model 42 and thedeformed patient-specific anatomical model 40, a predicted value of ameasure of hemodynamic compromise. In this example, the determinationunit 22 determines a predicted value of a measure of obstruction of thesecond blood flow path 48 in the deformed patient-specific anatomicalmodel 40. In this example the determination unit 22 is arranged fordetermining a cross sectional area of the second blood flow path 48after deployment of the implant model 42. Thereto the determination unit22 can determine the deformation of the implant model 42 and thepatient-specific anatomical model 40 due to deployment, and possiblepost-dilation. The deformations of both models 40, 42, in conjunctionwith modeled elasticities of the models 40, 42, allow to determine theforce exerted by the one model onto the other. The elasticities of themodels can be modeled as stiffnesses between nodes of the respectivemodels.

Additionally, the determination unit 22 can be operated for determininga cross sectional area of the second blood flow path 48 beforedeployment of the implant model 42. Hence a difference in crosssectional area before and after deployment of the implant model 42 canbe determined. The difference can be a measure for obstruction of thesecond blood flow path 48 due to presence of the implant model 42 anddeformation of the patient-specific anatomical model 40. Alternatively,or additionally, the measure of obstruction of the second blood flowpath 48 can be determined as a ratio of the cross sectional area of thesecond blood flow path 48 when the implant model 42 is deployed dividedby the cross sectional area of the second blood flow path 48 in thepatient-specific anatomical model 40 in which no implant model 42 isdeployed.

In the above example, the determined hemodynamic compromise includesobstruction of the second blood flow path 48. Alternatively, oradditionally, the determined hemodynamic compromise includes obstructionof the first blood flow path 46. It will be appreciated that the firstblood flow path 46 may be somewhat obstructed by the presence of theimplant. Thus, the calculation unit 21 can calculate a deformation ofthe patient-specific anatomical model 40 as a result of implant model 42deployment. The determination unit 22 can be operated for determining across sectional area of the first blood flow path 46. This may e.g. becompared to a cross sectional area of the first blood flow path 46before deployment of the implant model 42. Hence, the determination unit22 can determine a measure of obstruction of the first blood flow path.It will be appreciated that possibly the way in which the implant isdeployed in the first blood flow path 46 affects positioning of leaflets43 of the implant model 42. Possibly the leaflets 43 do not fully open.Thereto, the determination unit 22 can calculate leaflet 43 position inthe opened position. Thus, the determination unit 22 can take leaflet 43positioning into account for determining an open area of the first bloodflow path 46 for determining the measure of obstruction.

Alternatively, or additionally, the determination unit 22 can determinea pressure drop in the first blood flow path 46 along the implant model42. The pressure drop is also representative for obstruction of thefirst blood flow path 46 due to the implant model 42.

Alternatively, or additionally, the determined hemodynamic compromiseincludes leakage of blood in the first blood flow path. For example, itis possible that with the implant valve leaflets 43 closed blood leaksaround the outside of the implanted valve, between the valve and thesurrounding tissue. Then, from the virtually deployed implant model 42and the deformed patient-specific anatomical model 40, the determinationunit 22 can determine a measure of leakage in the first blood flow pathin the deformed patient-specific anatomical model. Thereto, thedetermination unit 22 can use calculated fluid pressures in the cardiacregion. It is also possible to use computational fluid dynamics, CFD.

It is also possible that the implant valve leaflets 43 do not fullyclose due to the way in which the implant is deployed in the first bloodflow path 46. This too may result in leakage of blood, in the closedposition of the leaflets 43. Thereto, the determination unit 22 cancalculate leaflet 43 position in the closed position. Thus, thedetermination unit 22 can calculate leakage.

The processing unit 2 can further include an assessment unit 24 arrangedfor determining a measure of risk of the patient developing hemodynamicproblems, such as second blood flow path obstruction on the basis of thedetermined deformed models 40, 42. The determined risk can e.g. beexpressed as a percentage, a number, a level or the like. The processingunit 2 is communicatively connectable to a presentation unit 26. Thepresentation unit 26 in this example is a display to display the measureof risk of the patient developing hemodynamic compromise to a user. Itwill be appreciated that the presentation unit can also present arepresentation, such as a numerical and/or graphical representation, ofthe obstruction to the user. Alternative, or additional, presentationunits could be used, such as a hardcopy printer, an email server, amessage service, a speaker device, etc.

It will be appreciated that the processing unit 2 may be arranged forapplying a calibration. Thereto the processing unit 2 can include acalibration unit 28. Optionally, the predicted measure of hemodynamiccompromise is determined for a plurality of patients. For each of thesepatients the predicted measure of hemodynamic compromise and theoccurring or not-occurring of hemodynamic problems in reality are storedin a calibration database. From this calibration database a correlationbetween the predicted measure of hemodynamic compromise and theoccurrence of hemodynamic problems in real life can be determined. Fromthe correlation a measure of risk of the patient developing hemodynamicproblems on the basis of the determined hemodynamic compromise can bedetermined. It will be appreciated that the calibration database can beupdated over time.

FIGS. 3a, 3b, 3c show an example wherein the implant model 42 is placedinto the patient-specific anatomical model 40 at a plurality ofdifferent locations. In this example the patient-specific anatomicalmodel 40 includes the region around the mitral valve 50. Here the firstblood flow path 44 extends through the mitral valve 50. The second bloodflow path 46 is formed by the LVOT and prolongs into the aorta. Thenative valve leaflets 52 can be identified in the FIGS. 3a-3c . In thisexample going from FIGS. 3a to 3b to 3c the implant model 42 is placedat three positions which are successively shifted by a few millimetersalong the mitral valve. Thereto the processing unit 2 includes aposition variation unit 30. As can be seen in the example of FIG. 3a ,the tips 53 of the native valve leaflets 52 are freely overhanging theimplant model 42. In 3 c the native valve leaflets 52, including theirtips 53, are pressed against the LVOT. Therefore, going from FIG. 3a toFIG. 3c the obstruction gradually increases.

The assessment unit 24 determines the measure of obstruction for each ofthe different locations. From this analysis a user can learn whichposition of the implant provides the lowest risk of the patientdeveloping hemodynamic problems. This information can be used inplanning of the TMVR procedure. It is also possible that the processingunit 2 selects the position of the implant providing the lowest riskmeasure of hemodynamic problems. The processing unit can present theselected position as preferred the deployment site 44.

It will be appreciated that it is also possible that a plurality ofdifferent implant models 42 is provided. Each implant model 42 canrepresent geometrical and/or material properties of a correspondingreal-life implant. The implant models 42 may e.g. differ in size, brand,construction, material or the like. Each of the implant models can thenbe placed into the patient specific anatomical model 40. The measure ofhemodynamic compromise, and/or the risk of the patient developinghemodynamic problems, is then determined for each of the implant models42. From this analysis it can be determined which one of the pluralityof implant models has associated therewith the lowest measure ofhemodynamic compromise and/or the lowest risk of the patient developinghemodynamic problems. A cardiac valve implant corresponding to theimplant model 42 having the lowest associated measure of hemodynamiccompromise and/or risk of the patient developing hemodynamic problemscan then be selected for a real-life percutaneous implantationprocedure. It will be appreciated that it is also possible that each ofthe implant models 42 is placed into the patient-specific anatomicalmodel 40 at a plurality of different locations. Thus for each implantmodel a position of lowest hemodynamic compromise and/or risk can bedetermined. The lowest compromise and/or risk per implant model 42 canthen be compared to select the cardiac valve implant for real-lifepercutaneous implantation.

It is also possible that the patient-specific model 40 includes timeinformation. The patient-specific model may include a plurality ofviews, each corresponding to a different moment during the cardiaccycle. The measure of hemodynamic compromise for the implant model canbe determined for each of the views. Hence, the measure of hemodynamiccompromise can be determined at different moments during the cardiaccycle.

It will be appreciated that it is also possible that each of the implantmodels 42 is placed into the patient-specific anatomical model 40 at aplurality of different locations and analyzed for each of the views.Thus for each implant model a lowest measure of hemodynamic compromiseand/or risk can be determined among the different locations and duringthe cardiac cycle. Also for each implant model a highest measure ofhemodynamic compromise and/or risk can be determined among the differentlocations and during the cardiac cycle. The lowest and highesthemodynamic compromise and/or risk per implant model 42 can then becompared to select the cardiac valve implant for real-life percutaneousimplantation. As can be seen in FIGS. 2 and 3 a-3 d, parts of theanatomy of the cardiac region may also contribute to the obstruction.For example the pressure of blood flowing through the first and/orsecond blood flow path can affect a position of parts of the anatomy,such as (calcified) native valve leaflets. According to an aspect, thecalculation unit 21 calculates the deformation of the patient-specificanatomical model 40 as a result of implant model 42 deployment and fluidpressure. The interaction of the fluid and the structures of thepatient-specific anatomical model can be included (fluid structureinteraction, FSI) in the calculation of the deformed patient-specificanatomical model. Also computational fluid dynamics, CFD, can be usedfor determining the deformation of the patient-specific anatomical model40 as a result of implant model 42 deployment and fluid mechanics insidethe blood flow paths.

Herein, the invention is described with reference to specific examplesof embodiments of the invention. It will, however, be evident thatvarious modifications and changes may be made therein, without departingfrom the essence of the invention. For the purpose of clarity and aconcise description features are described herein as part of the same orseparate embodiments, however, alternative embodiments havingcombinations of all or some of the features described in these separateembodiments are also envisaged.

It will be appreciated that in each of the examples, and in general,determining the measure of hemodynamic compromise may includedetermining a plurality of situations of progressing deployment of theimplant model into the patient-specific anatomical model. The situationsmay progressively differ by a predetermined amount or ratio ofdeployment. The deployment can include insertion of the implant modelinto the patient-specific anatomical model. The insertion can includetravel of a model of a, collapsed, implant along a vessel. Thesituations can include progressively differing positions of insertion upto the intended deployment position. The deployment can includeexpansion of the implant model in the patient-specific anatomical model.The situations can include progressively differing stages of expansionof the implant model. For each of the situations the measure ofhemodynamic compromise can be determined as described above. Hence, allstages of deployment can be modeled. The processing unit may be arrangedto determine the situation of the plurality of situations in which thedetermined hemodynamic compromise is least significant, e.g. lowest, ormost significant, e.g. highest. The processing unit may be arranged todetermine the measure of hemodynamic compromise in the situation of theplurality of situations in which the determined hemodynamic compromiseis least or most significant for predicting hemodynamic problems.

It will be appreciated that such determining of a plurality ofsituations simulates determining an evolution of the measure ofhemodynamic compromise between the implant model and thepatient-specific anatomical model over time during the process ofdeployment.

It will be appreciated that simulating an evolution of the measure ofhemodynamic compromise over time, may also be performed for a period oftime after deployment, such as days, weeks, months, or even years afterdeployment. As such, remodeling of the heart, due to the heart anatomychanging due to the prolonged presence of the implant, can be taken intoaccount.

In the examples, the implant model comprises a finite element model. Itwill be appreciated that it is also possible that the implant modelcomprises a mesh-free model. In the examples, the patient-specificanatomical model comprises a finite element model. It will beappreciated that it is also possible that the patient-specificanatomical model comprises a mesh-free model. It will be appreciatedthat the processing unit, first receiving unit, conversion unit, secondreceiving unit, input unit, modelling system, placing unit, calculationunit, determination unit, assessment unit, presentation unit, and/orposition variation unit can be embodied as dedicated electroniccircuits, possibly including software code portions. The processingunit, first receiving unit, conversion unit, second receiving unit,input unit, modelling system, placing unit, calculation unit,determination unit, assessment unit, presentation unit, and/or positionvariation unit can also be embodied as software code portions executedon, and e.g. stored in, a memory of, a programmable apparatus such as acomputer, tablet or smartphone.

Although the embodiments of the invention described with reference tothe drawings comprise computer apparatus and processes performed incomputer apparatus, the invention also extends to computer programs,particularly computer programs on or in a carrier, adapted for puttingthe invention into practice. The program may be in the form of source orobject code or in any other form suitable for use in the implementationof the processes according to the invention. The carrier may be anyentity or device capable of carrying the program.

For example, the carrier may comprise a storage medium, such as a ROM,for example a CD ROM or a semiconductor ROM, or a magnetic recordingmedium, for example a floppy disc or hard disk. Further, the carrier maybe a transmissible carrier such as an electrical or optical signal whichmay be conveyed via electrical or optical cable or by radio or othermeans, e.g. via the internet or cloud.

When a program is embodied in a signal which may be conveyed directly bya cable or other device or means, the carrier may be constituted by suchcable or other device or means. Alternatively, the carrier may be anintegrated circuit in which the program is embedded, the integratedcircuit being adapted for performing, or for use in the performance of,the relevant processes.

However, other modifications, variations, and alternatives are alsopossible. The specifications, drawings and examples are, accordingly, tobe regarded in an illustrative sense rather than in a restrictive sense.

For the purpose of clarity and a concise description features aredescribed herein as part of the same or separate embodiments, however,it will be appreciated that the scope of the invention may includeembodiments having combinations of all or some of the featuresdescribed.

In the claims, any reference sign placed between parentheses shall notbe construed as limiting the claim. The word ‘comprising’ does notexclude the presence of other features or steps than those listed in aclaim. Furthermore, the words ‘a’ and ‘an’ shall not be construed aslimited to ‘only one’, but instead are used to mean ‘at least one’, anddo not exclude a plurality. The mere fact that certain measures arerecited in mutually different claims does not indicate that acombination of these measures cannot be used to an advantage.

1. A computer-implemented method for pre-operative planning for deliveryof a prosthetic cardiac implant to a patient's heart, the methodcomprising: obtaining a plurality of digital images of a patient'sheart; obtaining a digital three-dimensional model of a prostheticcardiac implant; generating, from the plurality of digital images, adigital patient-specific anatomical model representing apatient-specific cardiac region including a deployment site for theprosthetic cardiac implant; virtually deploying the digitalthree-dimensional model of the prosthetic cardiac implant at thedeployment site; calculating deformation of the digitalthree-dimensional model of the prosthetic cardiac implant, in thedeployed state, within the deployment site of the patient-specificcardiac region; and determining a measure of interaction between thedigital three-dimensional model of the prosthetic cardiac implant andthe patient-specific cardiac region of the digital patient-specificanatomical model.
 2. The computer-based method of claim 1, whereindetermining a measure of interaction comprises determining a blood flowpath associated with the digital three-dimensional model of theprosthetic cardiac implant and the patient-specific cardiac region ofthe digital patient-specific anatomical model.
 3. The computer-basedmethod of claim 1, wherein determining a measure of interactioncomprises determining a measure of leakage in or around a perimeter ofthe digital three-dimensional model of the prosthetic cardiac implant.4. The computer-based method of claim 1, further comprising providingthe patient-specific digital anatomical model of the patient-specificcardiac region at a plurality of moments during a cardiac cycle, andwherein the measure of interaction is determined at the plurality ofmoments.
 5. The computer-based method of claim 1, further comprisingdetermining the measure of interaction after simulating remodeling ofthe patient-specific digital anatomical model of the patient-specificcardiac region caused by prolonged presence of the digitalthree-dimensional model of the prosthetic cardiac implant.
 6. Thecomputer-based method of claim 1, wherein determining the measure ofinteraction comprises determining a degree of incomplete deployment ofthe digital three-dimensional model of the prosthetic cardiac implant.7. The computer-based method of claim 1, wherein the digitalthree-dimensional model of the prosthetic cardiac implant is a digitalthree-dimensional model of a prosthetic heart valve.
 8. Thecomputer-based method of claim 1, wherein the digital three-dimensionalmodel of the prosthetic cardiac implant is a digital three-dimensionalmodel of a left atrial appendage closure device.
 9. The computer-basedmethod of claim 1, wherein determining the measure of interactioncomprises determining a measure of hemodynamic compromise associatedwith deploying the digital three-dimensional model of the prostheticcardiac implant at the deployment site.
 10. The computer-based method ofclaim 1, wherein the digital three-dimensional model of the prostheticcardiac implant is selected to block clots from going into abloodstream.
 11. The computer-based method of claim 1, furthercomprising virtually deploying the digital three-dimensional model ofthe prosthetic cardiac implant into the patient-specific digitalanatomical model of the cardiac region at a plurality of differentlocations and determining the measure of interaction for each of theplurality of different locations.
 12. The computer-based method of claim1, wherein virtually deploying the digital three-dimensional model ofthe prosthetic cardiac implant further comprises: providing a pluralityof digital three-dimensional models of prosthetic cardiac implantshaving different geometrical or material properties; and virtuallydeploying each of the plurality of digital three-dimensional models ofprosthetic cardiac implants into the patient specific digital anatomicalmodel of the patient's cardiac region, and determining the measure ofinteraction for each of the plurality of digital three-dimensionalmodels of prosthetic cardiac implants.
 13. The computer-based method ofclaim 12, further comprising determining a corresponding one of theplurality of digital three-dimensional models of prosthetic cardiacimplants that causes a preferred degree of interaction as compared toothers of the plurality of digital three-dimensional models ofprosthetic cardiac implants.
 14. The computer-based method of claim 1,further comprising displaying the measure of interaction on a computersystem display and the digital three-dimensional model of the prostheticcardiac implant deployed at the deployment site.
 15. A system forpre-operative planning for delivery of a prosthetic cardiac implant to apatient's heart, the system comprising at least one processor configuredto: obtain a plurality of digital images of a patient's heart; obtain adigital three-dimensional model of a prosthetic cardiac implant;generate, from the plurality of digital images, a digitalpatient-specific anatomical model representing a patient-specificcardiac region including a deployment site for the prosthetic cardiacimplant; virtually deploy the digital three-dimensional model of theprosthetic cardiac implant at the deployment site; calculate deformationof the digital three-dimensional model of the prosthetic cardiacimplant, in the deployed state, within the deployment site of thepatient-specific cardiac region; and determine a measure of interactionbetween the digital three-dimensional model of the prosthetic cardiacimplant and the patient-specific cardiac region of the digitalpatient-specific anatomical model.
 16. The system of claim 15, whereinthe digital three-dimensional model of the prosthetic cardiac implant isa digital three-dimensional model of a prosthetic heart valve.
 17. Thesystem of claim 15, wherein the digital three-dimensional model of theprosthetic cardiac implant is a digital three-dimensional model of aleft atrial appendage closure device.
 18. The system of claim 15,wherein the system is further configured to virtually deploy the digitalthree-dimensional model of the prosthetic cardiac implant into thepatient-specific digital anatomical model of the cardiac region at aplurality of different locations and determine the measure ofinteraction for each of the plurality of different locations.
 19. Thesystem of claim 15, wherein the virtually deployment of the digitalthree-dimensional model of the prosthetic cardiac implant furthercomprises: provide a plurality of digital three-dimensional models ofprosthetic cardiac implants having different geometrical or materialproperties; and virtually deploy each of the plurality of digitalthree-dimensional models of prosthetic cardiac implants into the patientspecific digital anatomical model of the patient's cardiac region, anddetermine the measure of interaction for each of the plurality ofdigital three-dimensional models of prosthetic cardiac implants.
 20. Thesystem of claim 19, wherein the system is further configured todetermine a corresponding one of the plurality of digitalthree-dimensional models of prosthetic cardiac implants that causes apreferred degree of interaction as compared to others of the pluralityof digital three-dimensional models of prosthetic cardiac implants. 21.A non-transitory computer-readable medium storing computer implementableinstructions that when executed by a programmable computer cause thecomputer to: obtain a plurality of digital images of a patient's heart;obtain a digital three-dimensional model of a prosthetic cardiacimplant; generate, from the plurality of digital images, a digitalpatient-specific anatomical model representing a patient-specificcardiac region including a deployment site for the prosthetic cardiacimplant; virtually deploy the digital three-dimensional model of theprosthetic cardiac implant at the deployment site; calculate deformationof the digital three-dimensional model of the prosthetic cardiacimplant, in the deployed state, within the deployment site of thepatient-specific cardiac region; and determine a measure of interactionbetween the digital three-dimensional model of the prosthetic cardiacimplant and the patient-specific cardiac region of the digitalpatient-specific anatomical model.